Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing.

N6-methyladenosine (m6A) is the most abundant internal eukaryotic mRNA modification, and is involved in the regulation of various biological processes. Direct Nanopore sequencing of native RNA (dRNA-seq) emerged as a leading approach for its identification. Several software were published for m6A detection and there is a strong need for independent studies benchmarking their performance on data from different species, and against various reference datasets. Moreover, a computational workflow is needed to streamline the execution of tools whose installation and execution remains complicated. We developed NanOlympicsMod, a Nextflow pipeline exploiting containerized technology for comparing 14 tools for m6A detection on dRNA-seq data. NanOlympicsMod was tested on dRNA-seq data generated from in vitro (un)modified synthetic oligos. The m6A hits returned by each tool were compared to the m6A position known by design of the oligos. In addition, NanOlympicsMod was used on dRNA-seq datasets from wild-type and m6A-depleted yeast, mouse and human, and each tool's hits were compared to reference m6A sets generated by leading orthogonal methods. The performance of the tools markedly differed across datasets, and methods adopting different approaches showed different preferences in terms of precision and recall. Changing the stringency cut-offs allowed for tuning the precision-recall trade-off towards user preferences. Finally, we determined that precision and recall of tools are markedly influenced by sequencing depth, and that additional sequencing would likely reveal additional m6A sites. Thanks to the possibility of including novel tools, NanOlympicsMod will streamline the benchmarking of m6A detection tools on dRNA-seq data, improving future RNA modification characterization.

A Regulatory Axis between Epithelial Splicing Regulatory Proteins and Estrogen Receptor α Modulates the Alternative Transcriptome of Luminal Breast Cancer.

Epithelial splicing regulatory proteins 1 and 2 (ESRP1/2) control the splicing pattern during epithelial to mesenchymal transition (EMT) in a physiological context and in cancer, including breast cancer (BC). Here, we report that ESRP1, but not ESRP2, is overexpressed in luminal BCs of patients with poor prognosis and correlates with estrogen receptor α (ERα) levels. Analysis of ERα genome-binding profiles in cell lines and primary breast tumors showed its binding in the proximity of ESRP1 and ESRP2 genes, whose expression is strongly decreased by ERα silencing in hormone-deprived conditions. The combined knock-down of ESRP1/2 in MCF-7 cells followed by RNA-Seq, revealed the dysregulation of 754 genes, with a widespread alteration of alternative splicing events (ASEs) of genes involved in cell signaling, metabolism, cell growth, and EMT. Functional network analysis of ASEs correlated with ESRP1/2 expression in ERα+ BCs showed RAC1 as the hub node in the protein-protein interactions altered by ESRP1/2 silencing. The comparison of ERα- and ESRP-modulated ASEs revealed 63 commonly regulated events, including 27 detected in primary BCs and endocrine-resistant cell lines. Our data support a functional implication of the ERα-ESRP1/2 axis in the onset and progression of BC by controlling the splicing patterns of related genes.

Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data.

Recent improvements in cost-effectiveness of high-throughput technologies has allowed RNA sequencing of total transcriptomes suitable for evaluating the expression and regulation of circRNAs, a relatively novel class of transcript isoforms with suggested roles in transcriptional and post-transcriptional gene expression regulation, as well as their possible use as biomarkers, due to their deregulation in various human diseases. A limited number of integrated workflows exists for prediction, characterization, and differential expression analysis of circRNAs, none of them complying with computational reproducibility requirements. We developed Docker4Circ for the complete analysis of circRNAs from RNA-Seq data. Docker4Circ runs a comprehensive analysis of circRNAs in human and model organisms, including: circRNAs prediction; classification and annotation using six public databases; back-splice sequence reconstruction; internal alternative splicing of circularizing exons; alignment-free circRNAs quantification from RNA-Seq reads; and differential expression analysis. Docker4Circ makes circRNAs analysis easier and more accessible thanks to: (i) its R interface; (ii) encapsulation of computational tasks into docker images; (iii) user-friendly Java GUI Interface availability; and (iv) no need of advanced bash scripting skills for correct use. Furthermore, Docker4Circ ensures a reproducible analysis since all its tasks are embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project.

The expression of LINE1-MET chimeric transcript identifies a subgroup of aggressive breast cancers.

Demethylation of the long interspersed nuclear element (LINE-1; L1) antisense promoter can result in transcription of neighboring sequences as for the L1-MET transcript produced by the L1 placed in the second intron of MET. To define the role of L1-MET, we investigated the sequence and the transcription of L1-MET in vitro models and heterogeneous breast cancers, previously reported to show other L1-derived transcripts. L1-MET expressing cell lines were initially identified in silico and investigated for L1-MET promoter methylation, cDNA sequence and cell fraction mRNA. The transcriptional level of L1-MET and MET were then evaluated in breast specimens, including 9 cancer cell lines, 41 carcinomas of different subtypes, and 11 normal tissues. In addition to a L1-MET transcript ending at MET exon 21, six novel L1-MET splice variants were identified. Normal breast tissues were negative for the L1-MET expression, whereas the triple-negative breast cancer (TNBC) and the high-grade carcinomas were enriched with the L1-MET mRNA (p = 0.005 and p = 0.018, respectively). In cancer cells and tissues the L1-MET expression was associated with its promoter hypomethylation (ρ = -0.8 and -0.9, respectively). No correlation was found between L1-MET and MET mRNA although L1-MET expressing tumors with higher L1-MET/MET ratio were negative for the MET protein expression (p = 0.006). Besides providing the first identification and detailed description of L1-MET in breast cancer, we clearly demonstrate that higher levels of this transcript specifically recognize a subset of more aggressive carcinomas, mainly TNBC. We suggest the possible evaluation of L1-MET in the challenging diagnosis of early TNBCs.

Nanodynamo quantifies subcellular RNA dynamics revealing extensive coupling between steps of the RNA life cycle.

The coordinated action of transcriptional and post-transcriptional machineries shapes gene expression programs at steady state and determines their concerted response to perturbations. We have developed Nanodynamo, an experimental and computational workflow for quantifying the kinetic rates of nuclear and cytoplasmic steps of the RNA life cycle. Nanodynamo is based on mathematical modelling following sequencing of native RNA from cellular fractions and polysomes. We have applied this workflow to triple-negative breast cancer cells, revealing widespread post-transcriptional RNA processing that is mutually exclusive with its co-transcriptional counterpart. We used Nanodynamo to unravel the coupling between transcription, processing, export, decay and translation machineries. We have identified a number of coupling interactions within and between the nucleus and cytoplasm that largely contribute to coordinating how cells respond to perturbations that affect gene expression programs. Nanodynamo will be instrumental in unravelling the determinants and regulatory processes involved in the coordination of gene expression responses.

News from around the RNA world: new avenues in RNA biology, biotechnology and therapeutics from the 2022 SIBBM meeting.

Since the formalization of the Central Dogma of molecular biology, the relevance of RNA in modulating the flow of information from DNA to proteins has been clear. More recently, the discovery of a vast set of non-coding transcripts involved in crucial aspects of cellular biology has renewed the enthusiasm of the RNA community. Moreover, the remarkable impact of RNA therapies in facing the COVID19 pandemics has bolstered interest in the translational opportunities provided by this incredible molecule. For all these reasons, the Italian Society of Biophysics and Molecular Biology (SIBBM) decided to dedicate its 17th yearly meeting, held in June 2022 in Rome, to the many fascinating aspects of RNA biology. More than thirty national and international speakers covered the properties, modes of action and applications of RNA, from its role in the control of development and cell differentiation to its involvement in disease. Here, we summarize the scientific content of the conference, highlighting the take-home message of each presentation, and we stress the directions the community is currently exploring to push forward our comprehension of the RNA World 3.0.

Luminal breast cancer-specific circular RNAs uncovered by a novel tool for data analysis.

Circular RNAs are highly stable molecules present in all eukaryotes generated by distinct transcript processing. We have exploited poly(A-) RNA-Seq data generated in our lab in MCF-7 breast cancer cells to define a compilation of exonic circRNAs more comprehensive than previously existing lists. Development of a novel computational tool, named CircHunter, allowed us to more accurately characterize circRNAs and to quantitatively evaluate their expression in publicly available RNA-Seq data from breast cancer cell lines and tumor tissues. We observed and confirmed, by ChIP analysis, that exons involved in circularization events display significantly higher levels of the histone post-transcriptional modification H3K36me3 than non-circularizing exons. This result has potential impact on circRNA biogenesis since H3K36me3 has been involved in alternative splicing mechanisms. By analyzing an Ago-HITS-CLIP dataset we also found that circularizing exons overlapped with an unexpectedly higher number of Ago binding sites than non-circularizing exons. Finally, we observed that a subset of MCF-7 circRNAs are specific to tumor versus normal tissue, while others can distinguish Luminal from other tumor subtypes, thus suggesting that circRNAs can be exploited as novel biomarkers and drug targets for breast cancer.

A Novel Functional Domain of Tab2 Involved in the Interaction with Estrogen Receptor Alpha in Breast Cancer Cells.

Tab2, originally described as a component of the inflammatory pathway, has been implicated in phenomena of gene de-repression in several contexts, due to its ability to interact with the NCoR corepressor. Tab2 interacts also with steroid receptors and dismisses NCoR from antagonist-bound Estrogen and Androgen Receptors on gene regulatory regions, thus modifying their transcriptional activity and leading to pharmacological resistance in breast and prostate cancer cells. We demonstrated previously that either Tab2 knock-down, or a peptide mimicking the Estrogen Receptor alpha domain interacting with Tab2, restore the antiproliferative response to Tamoxifen in Tamoxifen-resistant breast cancer cells. In this work, we map the domain of Tab2 responsible of Estrogen Receptor alpha interaction. First, using both co-immunoprecipitation and pull-down with recombinant proteins, we found that the central part of Tab2 is primarily responsible for this interaction, and that this region also interacts with Androgen Receptor. Then, we narrowed down the essential interaction region by means of competition assays using recombinant protein pull-down. The interaction motif was finally identified as a small region adjacent to, but not overlapping, the Tab2 MEKK1 phosphorylation sites. A synthetic peptide mimicking this motif efficiently displaced Tab2 from interacting with recombinant Estrogen Receptor alpha in vitro, prompting us to test its efficacy using derivatives of the MCF7 breast carcinoma cell lines that are spontaneously resistant to Tamoxifen. Indeed, we observed that this mimic peptide, made cell-permeable by addition of the TAT minimal carrier domain, reduced the growth of Tamoxifen-resistant MCF7 cells in the presence of Tamoxifen. These data indicate a novel functional domain of the Tab2 protein with potential application in drug design.